With the Integrated Energy and Climate Programme (IEKP) of the German Government 175 TWh (68 GW) power from renewable energy sources are expected until 2020. Wind energy plays a key role achieving this goal. From 1998 to 2008 the annual wind power production in Germany has increased from 4.5 TWh (2.9 GW) to 39.5 TWh (22.2 GW) and with the IEKP additional 48 TWh (16 GW) wind power are assumed until 2020.

To assess the interaction of renewable power and conventional power, it is essential to model their load profiles. Hence, methods are presented for modelling the consumer load and load curves for renewable power and combined-heat-and-power plants for the year 2020. The conventional power plants have to fulfil the need of the residual load, which is defined as the consumer load minus the production of the must-run plants. Interesting days in the year 2020 with a negative residual load or high gradients are examined.

In contrast to conventional power production (defined as thermal power plants and controllable hydropower plants), which can be scheduled, wind power can only be forecasted. In case of an incorrect wind power forecast the power gap or surplus has to be balanced by conventional power plants. Hence, the accuracy of wind power forecast in 2008 is analysed in regard to interesting days (offset errors, time-shift errors, high forecast errors), frequency distribution and the root mean square deviation (RMSD) of the forecast errors, the medial forecast error as a function of the forecasted power and the RMSD of the forecast errors as a function of the forecast period.

A tool named ProFeT has been developed to synthesize the chronological sequence of wind power forecast errors in 2020. The frequency distributions of the forecast errors in 2008 and 2020 are compared. To assess the interaction of conventional power production and renewable power, the forecast errors in relation to the residual load is regarded.

After the proposition of the Bundesnetzagentur the power for balancing forecast errors should be covered in the intraday market. Hence, the intraday market at the European Energy Exchange has been examined in regard to traded volume, the frequency distribution of the price differences between intraday and day-ahead market, the price difference as a function of the forecast error and as function of the traded volume.